{"id":"https://openalex.org/W4387421411","doi":"https://doi.org/10.1145/3577190.3614115","title":"Neural Mixed Effects for Nonlinear Personalized Predictions","display_name":"Neural Mixed Effects for Nonlinear Personalized Predictions","publication_year":2023,"publication_date":"2023-10-07","ids":{"openalex":"https://openalex.org/W4387421411","doi":"https://doi.org/10.1145/3577190.3614115"},"language":"en","primary_location":{"id":"doi:10.1145/3577190.3614115","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3577190.3614115","pdf_url":null,"source":{"id":"https://openalex.org/S4363608440","display_name":"INTERNATIONAL CONFERENCE ON MULTIMODAL INTERACTION","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"INTERNATIONAL CONFERENCE ON MULTIMODAL INTERACTION","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.1145/3577190.3614115","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5017680583","display_name":"Torsten W\u00f6rtwein","orcid":"https://orcid.org/0009-0003-5659-029X"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Torsten W\u00f6rtwein","raw_affiliation_strings":["Language Technologies Institute, Carnegie Mellon University, United States"],"raw_orcid":"https://orcid.org/0009-0003-5659-029X","affiliations":[{"raw_affiliation_string":"Language Technologies Institute, Carnegie Mellon University, United States","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063313898","display_name":"Nicholas B. Allen","orcid":"https://orcid.org/0000-0002-1086-6639"},"institutions":[{"id":"https://openalex.org/I181233156","display_name":"University of Oregon","ror":"https://ror.org/0293rh119","country_code":"US","type":"education","lineage":["https://openalex.org/I181233156"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nicholas B. Allen","raw_affiliation_strings":["Center for Digital Mental Health, University of Oregon, United States"],"raw_orcid":"https://orcid.org/0000-0002-1086-6639","affiliations":[{"raw_affiliation_string":"Center for Digital Mental Health, University of Oregon, United States","institution_ids":["https://openalex.org/I181233156"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072586640","display_name":"Lisa Sheeber","orcid":"https://orcid.org/0000-0003-1293-943X"},"institutions":[{"id":"https://openalex.org/I1322437667","display_name":"Oregon Research Institute","ror":"https://ror.org/05j91v252","country_code":"US","type":"nonprofit","lineage":["https://openalex.org/I1322437667"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Lisa B. Sheeber","raw_affiliation_strings":["Oregon Research Institute, United States"],"raw_orcid":"https://orcid.org/0000-0003-1293-943X","affiliations":[{"raw_affiliation_string":"Oregon Research Institute, United States","institution_ids":["https://openalex.org/I1322437667"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071174795","display_name":"Randy P. Auerbach","orcid":"https://orcid.org/0000-0003-2319-4744"},"institutions":[{"id":"https://openalex.org/I78577930","display_name":"Columbia University","ror":"https://ror.org/00hj8s172","country_code":"US","type":"education","lineage":["https://openalex.org/I78577930"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Randy P. Auerbach","raw_affiliation_strings":["Department of Psychiatry, Columbia University, United States"],"raw_orcid":"https://orcid.org/0000-0003-2319-4744","affiliations":[{"raw_affiliation_string":"Department of Psychiatry, Columbia University, United States","institution_ids":["https://openalex.org/I78577930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000246394","display_name":"Jeffrey F. Cohn","orcid":"https://orcid.org/0000-0002-9393-1116"},"institutions":[{"id":"https://openalex.org/I170201317","display_name":"University of Pittsburgh","ror":"https://ror.org/01an3r305","country_code":"US","type":"education","lineage":["https://openalex.org/I170201317"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jeffrey F. Cohn","raw_affiliation_strings":["Psychology, University of Pittsburgh, United States"],"raw_orcid":"https://orcid.org/0000-0002-9393-1116","affiliations":[{"raw_affiliation_string":"Psychology, University of Pittsburgh, United States","institution_ids":["https://openalex.org/I170201317"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5081398601","display_name":"Louis\u2010Philippe Morency","orcid":"https://orcid.org/0000-0001-6376-7696"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Louis-Philippe Morency","raw_affiliation_strings":["Language Technologies Institute, Carnegie Mellon University, United States"],"raw_orcid":"https://orcid.org/0000-0001-6376-7696","affiliations":[{"raw_affiliation_string":"Language Technologies Institute, Carnegie Mellon University, United States","institution_ids":["https://openalex.org/I74973139"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.5199,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.6168898,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"445","last_page":"454"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9957000017166138,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9957000017166138,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T13283","display_name":"Mental Health Research Topics","score":0.9894000291824341,"subfield":{"id":"https://openalex.org/subfields/3205","display_name":"Experimental and Cognitive Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9803000092506409,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.682780921459198},{"id":"https://openalex.org/keywords/nonlinear-system","display_name":"Nonlinear system","score":0.5974072217941284},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4984309673309326},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3747158348560333},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.09645339846611023}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.682780921459198},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.5974072217941284},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4984309673309326},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3747158348560333},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.09645339846611023},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3577190.3614115","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3577190.3614115","pdf_url":null,"source":{"id":"https://openalex.org/S4363608440","display_name":"INTERNATIONAL CONFERENCE ON MULTIMODAL INTERACTION","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"INTERNATIONAL CONFERENCE ON MULTIMODAL INTERACTION","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3577190.3614115","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3577190.3614115","pdf_url":null,"source":{"id":"https://openalex.org/S4363608440","display_name":"INTERNATIONAL CONFERENCE ON MULTIMODAL INTERACTION","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"INTERNATIONAL CONFERENCE ON MULTIMODAL INTERACTION","raw_type":"proceedings-article"},"sustainable_development_goals":[{"score":0.6700000166893005,"display_name":"Good health and well-being","id":"https://metadata.un.org/sdg/3"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W31693452","https://openalex.org/W1483118642","https://openalex.org/W1951724000","https://openalex.org/W1967495697","https://openalex.org/W2019710112","https://openalex.org/W2052789463","https://openalex.org/W2081283602","https://openalex.org/W2084577255","https://openalex.org/W2099813784","https://openalex.org/W2143104527","https://openalex.org/W2151791593","https://openalex.org/W2239141610","https://openalex.org/W2325093922","https://openalex.org/W2593581739","https://openalex.org/W2779582454","https://openalex.org/W2807126412","https://openalex.org/W2890256689","https://openalex.org/W2905472553","https://openalex.org/W2962565361","https://openalex.org/W2963530216","https://openalex.org/W2963535485","https://openalex.org/W3028047900","https://openalex.org/W3037651932","https://openalex.org/W3129778969","https://openalex.org/W3177017072","https://openalex.org/W3205552558","https://openalex.org/W4238846128","https://openalex.org/W4245666426","https://openalex.org/W4281734508","https://openalex.org/W4290875381","https://openalex.org/W4312345918","https://openalex.org/W4376130118"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052","https://openalex.org/W4402327032","https://openalex.org/W2382290278"],"abstract_inverted_index":{"Personalized":[0],"prediction":[1],"is":[2,20],"a":[3,9,36,70,139,143,173,181],"machine":[4,100],"learning":[5,101],"approach":[6],"that":[7,162],"predicts":[8],"person\u2019s":[10],"future":[11],"observations":[12,18],"based":[13],"on":[14,56,233],"their":[15],"past":[16],"labeled":[17],"and":[19,58,88,169,180],"typically":[21],"used":[22],"for":[23,62,201,206],"sequential":[24],"tasks,":[25],"e.g.,":[26],"to":[27,81,113,132,176,184,212,241],"predict":[28,177,185,213],"daily":[29,178],"mood":[30,179],"ratings.":[31],"When":[32],"making":[33],"personalized":[34],"predictions,":[35],"model":[37,203],"can":[38],"combine":[39],"two":[40,202],"types":[41],"of":[42,150,195,229],"trends:":[43],"(a)":[44],"trends":[45,61,84,239],"shared":[46],"across":[47,166],"people,":[48],"i.e.,":[49,65],"person-generic":[50,87],"trends,":[51,67],"such":[52,68],"as":[53,69],"being":[54],"happier":[55],"weekends,":[57],"(b)":[59],"unique":[60],"each":[63],"person,":[64],"person-specific":[66,89,115,120,135,222,231],"stressful":[71],"weekly":[72],"meeting.":[73],"Mixed":[74,128],"effect":[75,94],"models":[76,80,95,131],"are":[77,96,110],"popular":[78],"statistical":[79],"study":[82],"both":[83],"by":[85,102],"combining":[86],"parameters.":[90],"Though":[91],"linear":[92,114],"mixed":[93,156],"gaining":[97],"popularity":[98],"in":[99,138,142],"integrating":[103],"them":[104],"with":[105,154],"neural":[106,140,151,207],"networks,":[107],"these":[108,230],"integrations":[109],"currently":[111],"limited":[112],"parameters:":[116],"ruling":[117],"out":[118],"nonlinear":[119,134,155,221],"trends.":[121],"In":[122],"this":[123],"paper,":[124],"we":[125,160,198],"propose":[126],"Neural":[127],"Effect":[129],"(NME)":[130],"optimize":[133],"parameters":[136],"anywhere":[137],"network":[141,152],"scalable":[144],"manner1.":[145],"NME":[146,163,200],"combines":[147],"the":[148,191,218,234,242],"efficiency":[149],"optimization":[153],"effects":[157],"modeling.":[158],"Empirically,":[159],"observe":[161],"improves":[164],"performance":[165],"six":[167],"unimodal":[168],"multimodal":[170],"datasets,":[171],"including":[172,205],"smartphone":[174],"dataset":[175,183,236],"mother-adolescent":[182,235],"affective":[186,214,226],"state":[187,215],"sequences":[188,216],"where":[189,217],"half":[190],"mothers":[192],"experience":[193],"symptoms":[194],"depression.":[196],"Furthermore,":[197],"evaluate":[199],"architectures,":[204],"conditional":[208],"random":[209],"fields":[210],"(CRF)":[211],"CRF":[219],"learns":[220],"temporal":[223],"transitions":[224,232],"between":[225],"states.":[227],"Analysis":[228],"shows":[237],"interpretable":[238],"related":[240],"mother\u2019s":[243],"depression":[244],"symptoms.":[245]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
